fastText Quick Start Guide

Perform efficient fast text representation and classification with Facebooks fastText libraryKey FeaturesIntroduction to Facebooks fastText library for NLPPerform efficient word representations sentence classification vector representationBuild better more scalable solutions for text representation and classificationBook DescriptionFacebooks fastText library handles text representation and classification used for Natural Language Processing (NLP). Most organizations have to deal with enormous amounts of text data on a daily basis and gaining efficient data insights requires powerful NLP tools such as fastText. This book is your ideal introduction to fastText. You will learn how to create fastText models from the command line without the need for complicated code. You will explore the algorithms that fastText is built on and how to use them for word representation and text classification. Next you will use fastText in conjunction with other popular libraries and frameworks such as Keras TensorFlow and PyTorch. Finally you will deploy fastText models to mobile devices. By the end of this book you will have all the required knowledge to use fastText in your own applications at work or in projects.What you will learnCreate models using the default command line options in fastTextUnderstand the algorithms used in fastText to create word vectorsCombine command line text transformation capabilities and the fastText library to implement a training validation and prediction pipelineExplore word representation and sentence classification using fastTextUse Gensim and spaCy to load the vectors transform lemmatize and perform other NLP tasks efficientlyDevelop a fastText NLP classifier using popular frameworks such as Keras Tensorflow and PyTorchWho this book is forThis book is for data analysts data scientists and machine learning developers who want to perform efficient word representation and sentence classification using Facebooks fastText library. Basic knowledge of Python programming is required.